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, mathematics, physics, remote sensing and machine learning. Experience and skills · Strong interest in modelling, model-data integration, and remote sensing data analysis. · Knowledge of programming, remote
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apply a fast and efficient forest trait mapping and monitoring method based on the Invertible Forest Reflectance Model. A machine learning / deep learning framework will be explored and developed
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Developing statistical, graph, and/or machine learning models to study transaction networks, illicit transaction patterns, and DeFi protocol operations Creating and evaluating tools, documentation, and open
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group. We seek a candidate with expertise and/or interest in the following relevant fields: machine learning and cybersecurity. The candidate will the opportunity to work on a CORE project funded by
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framework to bridge this gap and enable organizations to confidently deploy secure GenAI solutions by evaluating the machine-learning models intrinsically, identifying components of an AI pipeline and their
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training unit: https://www.list.lu/en/research/project/forfus Do you want to know more about LIST? Check our website: https://www.list.lu/ How will you contribute? Your PhD work will focus on outdoor forest
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machine learning methods to investigate how ecosystem water stress and drought disturbances affect relevant forest ecosystem functioning at various scales. It will enable advanced assessment of forest
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21 Aug 2025 Job Information Organisation/Company University of Luxembourg Research Field Computer science » Computer systems Researcher Profile First Stage Researcher (R1) Country Luxembourg
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conducts research on the application and the impact of digital technologies like DLT/Blockchain, Digital Identities and Machine Learning/AI on organisations from both the private and public sectors
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Robotisation (PROMAR) group, headed by Matthias Rupp. The group develops fundamental and technological expertise in machine learning for materials science, including data-driven accelerated simulations and